Learning From the Hiatus

This blog post describes two recent papers on the relatively slow increase of global temperatures over the past decade and a half. It focuses on a paper by Kosaka and Xie, and further analyzes the data from Kosaka and Xie to explore issues of model accuracy and climate sensitivity. The evidence points toward transient climate response being slightly weaker than the CMIP5 model average. Natural variability appears to have caused the recent hiatus but appears not to have contributed significantly to the previous period of rapid warming.

First, global surface temperatures stopped rising. After a few years, some observers wondered what that meant about the accuracy of climate models. Most climate scientists weren’t concerned; occasional flat periods are to be expected.

Then temperatures stayed fairly flat. Climate scientists, to reassure everyone, began actually publishing papers pointing out that climate models predict occasional flat periods. One scientist said that for something odd to be going on, the flat period would have to last for more than fifteen years.

The problem was not just the temporary flat period. The longer the flat period lasted, the farther the observed temperatures deviated from most climate model projections, as tracked by Lucia and others. This raised the question of whether climate models were too sensitive to radiative forcing, either from Tyndall gases or in general.

Then the flat period lasted for more than fifteen years. It became clear that “these things happen” was not a sufficient answer, especially since “these things” happen very rarely in climate models. It became important to understand what causes these things to happen, and why models apparently don’t simulate them very well. Finally, scientists started investigating what’s become known as the global warming “hiatus”.

Note: I don’t like that term, because it’s only the atmospheric part of the globe that is enjoying a hiatus from global warming. The oceans continue to take up lots of extra heat, and the glaciers continue to melt. Call it an “atmospheric warming hiatus”, and I’ll be much happier.

I’m one of those scientists. In a blog post last year, I noted that El Niño has a large influence on year-to-year climate changes, but that if you sort each year according to whether it’s El Niño, neutral, or La Niña, and exclude years of major volcanic influence, there’s a steady warming trend all the way from the 1970s to the present day, with no sign of a hiatus. My analysis was motivated by Foster and Rahmsdorf (2011), who looked more closely at both natural variations and variations in forcing and came to a similar conclusion. Later analysis by Troy Masters questioned whether one could say for sure that there was no hiatus, and the issue remained open.

Two New Papers

This past week, two papers tackled the issue head-on.

The first, by Fyfe et al., is mostly just a commentary that shows how unusual recent global temperature trends are compared to climate model projections, and surveys possible reasons. Their analysis has El Niño responsible for only about 0.02-0.03 C/decade trend reduction. Other possible sources of discrepancy that Fyfe et al. list are stratospheric aerosols, stratospheric water vapor, errors in aerosol or solar climate forcing, an unusual episode of internal climate variability, or a problem with the models being too sensitive.

Before digging into Kosaka and Xie, let me explain how the two papers can come to such different conclusions. Mainly, they’re focusing on different things. Fyfe et al. are concerned with explanations for the discrepancy between model projections and observations, while Kosaka and Xie are concerned with explanations for the observed change in temperature trend. Second, they use very different techniques to estimate the impact of El Niño.

Fyfe et al. use a simple model for El Niño variations, with a single tunable parameter. They adjust the parameter to maximize the correlation between simple model output and detrended observed temperatures. The disadvantage of this approach is that by maximizing correlation, they do not necessarily maximize agreement. The magnitude of their modeled El Niño impact on global temperatures could be much less than the actual impact, and the correlation would still be fine. Still, the approach seemed to work okay in Fyfe et al. 2010.

Kosaka and Xie don’t have a tunable parameter. They used a full-blown coupled ocean-atmosphere climate model (GFDL CM2.1). In addition to looking at the standard output from a set of runs using estimated anthropogenic and natural forcing (HIST), they used two other ensemble sets. Both other sets had the sea surface temperatures in the tropical central and eastern Pacific constantly nudged toward their observed values. One also included forcing (POGA-H), while the other ensemble set did not (POGA-C).

The acronyms are reminiscent of Walt Kelly, but they’re standard, and stand for Prescribed Ocean, Global Atmosphere. The H runs include historical forcings, while the C runs are control runs without time-varying forcing. I’ve seen experiments like this before, mostly for things like understanding the role of El Niño in altering regional temperature, wind, or precipitation patterns.

Here’s a non-technical translation: the HIST simulation has all the climate forcings, but doesn’t know how or when El Niño or La Niña patterns will develop. The POGA-H simulation has all the climate forcings, plus the atmosphere and ocean are forced to respond to the actual evolution of sea surface temperatures associated with El Niño and La Niña as they actually happened during the past sixty-plus years.

What Kosaka and Xie Found

Kosaka and Xie find that the POGA-H run reproduces the hiatus, along with most other interannual variations in global surface temperature (correlation 0.97 since 1970). In addition, it reproduces most of the key observed regional variations in warming, both during the rapid rise of 1971-1997 and the hiatus period of 2002-2012. All of this, to me, is convincing evidence that any explanation for the hiatus must pass through the tropical central and eastern Pacific.

There are two possible explanations. One is that the natural variability in the central and eastern tropical Pacific (which is known to be quite variable) randomly happened to evolve in such a way that it favored a cooling trend in surface temperatures for the past fifteen or so years, one that was almost strong enough to offset the longer-term global warming trend. The second is that the particular evolution of surface temperature in the central and eastern tropical Pacific, rather than being independent of global warming, is actually being caused by it.

The implication of explanation number one is that the effect of natural variability will soon reverse and global atmospheric warming will resume at its previous pace. The implication of explanation number two is that for an extended but unknown period of time, the tropical Pacific will continue to evolve in a La Niña fashion, maintaining a slow rate of temperature rise for quite some time. Kosaka and Xie argue that explanation number one is more likely, and I agree. Several pieces of evidence point toward explanation number one and away from explanation number two, but none of them are conclusive at this point.

How Much Was Natural Variability?

It is reasonable to wonder whether the growing disagreement between model projections and observed surface temperatures, as analyzed by Fyfe et al., represents something wrong with the models or whether it can all be explained away by natural variability. If natural variability is suppressing atmospheric warming in recent years, doesn’t that mean that it would have been enhancing atmospheric warming during the preceding period?

Judith Curry got rather excited by some of the numbers in Kosaka and Xie. As she put it:

Compare the temperature increase between 1975-1998 (main warming period in the latter part of the 20th century) for both POGA H and POGA C:

POGA H: 0.68C (natural plus anthropogenic)

POGA C: 0.4C (natural internal variability only)

I’m not sure how good my eyeball estimates are, and you can pick other start/end dates. But no matter what, I am coming up with natural internal variability associated accounting for significantly MORE than half of the observed warming.

Like I said, my mind is blown. I have long argued that the pause was associated with the climate shift in the Pacific Ocean circulation, characterized by the change to the cool phase of the PDO. I have further argued that if this is the case, then the warming since 1976 was heavily juiced by the warm phase of the PDO. I didn’t know how to quantify this, but I thought that it might account for at least half of the observed warming, and hence my questioning of the IPCC’s highly confident attribution of ‘most’ to AGW.

Although this was not a specific conclusion of the paper (the focused on the period 2002-2012), the conclusion jumps out from their Fig 1 (and my eyeball analysis).

Curry’s mind-blowing reading of the paper is incorrect. What she missed is that POGA-C is not “natural internal variability only”. It’s “natural plus forced in the El Niño region of the Pacific”. There’s no “natural variability only” run to compare to. The other two runs are “forced everywhere” (HIST) and “anthropogenic everywhere plus natural variability in the El Niño region of the Pacific” (POGA-H).

In model-land, an imaginary world in which the model correctly simulates what would have happened in the tropical Pacific without natural variability, and the climate system behaves linearly, we can estimate “tropical central-east Pacific natural variability only”, or TPNV, by subtracting HIST from POGA-H. Alternatively, we can estimate “forced outside of the tropical central-east Pacific”, or FOTP by subtracting POGA-C from POGA-H.

Doing this requires the model output. So I’ve manually digitized the data from Fig. 1 of Kosaka and Xie. To test whether I’ve done this correctly, I compare their original figure with my emulation of it from my digitized data. They appear to match.

Figure 1a from Kosaka and Xie (Nature 2013). Original caption: Observed and simulated global temperature trends. Annual-mean time series based on observations, HIST and POGA-H. Anomalies are deviations from the 1980-1999 averages, except for HIST, for which the reference is the 1980-1999 average of POGA-H. Major volcanic eruptions are indicated. Shading represents 95% confidence interval of ensemble means. Bars on the right show the ranges of ensemble spreads of the 2002-2012 averages.

Okay, now to the trends. I’ll compute linear regression trends for 1975-2002 and 2002-2012.

1975-2002 Trend (C/decade) Total linear regression temperature change

Observed 0.19 0.51

HIST 0.23 0.61

POGA-H 0.21 0.57

POGA-C 0.07 0.19

TPNV -0.02 -0.04

NOTP 0.14 0.38

So according to the model, the tropical Pacific by itself was responsible for 0.19 C of warming, and all of that was due to the response of the tropical Pacific to radiative forcing. The effect of natural variability in the tropical Pacific on the linear trend over that period was very small and negative, a mere -0.04 C. So contrary to Curry’s mind-blowing first impression, the results of Kosaka and Xie imply that natural variability in the tropical Pacific did not contribute at all to the rapid warming from 1975 to 2002.

2002-2012 Trend (C/decade) (which is equal to the total linear temperature change over that time period)

Observed -0.04

HIST 0.20

POGA-H 0.03

POGA-C -0.13

TPNV -0.17

FOTP 0.16

So, according to the model, the central and eastern tropical Pacific was responsible for a -0.13 C decline in global temperatures. This consisted of a small positive forced contribution of 0.04 C and a natural variability component of -0.17 C. Meanwhile, forcing outside the tropical Pacific contributed a global increase of 0.16 C, so the net global temperature change was a mere 0.03 C.

Let’s look at the time series of POGA-C (the effect of natural and forced temperature changes in the central and eastern tropical Pacific) and TPNV (the effect of natural changes in the central and eastern tropical Pacific only, computed from POGA-H minus HIST). To better show differences, I’m plotting both as anomalies from the 1950-1970 period.

Annual values and 5-year running means of simulated global temperatures forced by combined natural and forced temperature changes in the central and eastern tropical Pacific (POGA-C) and by natural-only changes in the central and eastern tropical Pacific (TPNV, computed as POGA-H minus HIST). Anomalies are relative to 1950-1970 averages.

You can see how the combined effect of natural and forced temperature changes in the tropical Pacific contributes positively to atmospheric warming, while the effect of natural changes alone is a negative contribution to atmospheric warming.

Remember the speculation about whether these natural changes were truly natural? If they are natural, they should go up and down with little long-term trend. If they are at least partially forcing-triggered, they should include a long-term trend. As it turns out, the trend for the full simulation length of 1950-2012 for TPNV is -0.03 C/decade, which is not much. Then again, we’re talking about a highly nonlinear part of the climate system, and maybe it only kicks into cooling mode after a certain threshold is (recently) crossed. As I said before, the evidence points toward a mostly natural variation, but we don’t yet know for sure.

Is the GFDL CM2.1 Too Sensitive to Forcing?

Thanks to Kosaka and Xie, we now have a GFDL model run with f0rcing plus natural variability (POGA-H). As noted earlier, the correlation with observed climate variations is excellent. But does it have the right long-term trend?

We’ve already looked at two trend segments. For 1975-2002, the observed trend is 0.19 C/decade, and the POGA-H trend is 0.21 C/decade. For 2002-2012, the observed trend is -0.04 C/decade, and the POGA-H trend is 0.03 C/decade. In both segments, the POGA-H simulation warms too much.

Here’s the difference between observed and POGA-H for the full model simulation, along with the HIST simulation:

We see a systematic and steadily-changing difference between POGA-H and reality. The negative values indicate that POGA-H is overestimating the temperature trend. Compared to the 1950-1970 reference period, POGA-H has temperatures warming by 0.2 C more than reality. The steady evolution of the difference implies that caused by an erroneous model response rather than natural variability. Either the forcing being provided to the model is too strong, or the model is too sensitive.

If model sensitivity is the problem, we can use these results to estimate the Transient Climate Response (TCR) of the climate system. TCR is defined as a 20-year average of the temperature change in response to a steady increase of CO2 of 1%/year by the time that CO2 doubles. Recent rates of radiative forcing change are similar to the forcing change that would be associated with a 1%/year rise of CO2.

From forcing alone, the GFDL model predicts that temperatures should have risen by about 1.0 C since 1950-1970. From the POGA-H comparison to reality, we know that the model temperature response over that period is 0.2 C too strong. Therefore, the TCR of the climate system should be about 20% less than the TCR of the GFDL model. According to Forster et al. (2013), the TCR of the GFDL CM3 is 2.0 C. If this is the same model configuration that was used in Kosaka and Xie, the correct TCR would be 1.6 C.

[Update: It turns out that the sensitivity of GFDL CM2.1 is different from the sensitivity of GFDL CM3. See “Learning More From the Hiatus” for a corrected estimate of Transient Climate Response, including uncertainty estimates. – John N-G 9/2/13]

The TCR value of 1.6 C is close to but slightly smaller than the IPCC model mean of 1.82 C. So we find that the GFDL CM is somewhat too sensitive to climate forcing, and the average TCR of all models is only slightly too large.

Final Words

Be warned that the results from my analysis of Kosaka and Xie have not been subjected to peer review, even though Kosaka and Xie’s paper itself has been peer-reviewed. I welcome comments, suggestions, and corrections.

In a more recent blog entry, Judith Curry notes the discussions among IPCC nations regarding the draft report’s treatment of the atmospheric warming hiatus. Even though Kosaka and Xie have made a convincing (to me) argument for the cause of the hiatus, the paper was not completed in time to be included in the IPCC report, according to the IPCC rules. I do not envy the IPCC authors who have to deal with this issue.